Yihua Zhang

Yihua Zhang

First year Ph.D. student at Michigan State University
Email: zhan1908 At msu Dot edu
Research Interests
  • Adversarial Machine Learning
  • Scalable Machine Learning
  • Optimization Theories

About

Hi, I am Yihua Zhang (张逸骅), a first-year Ph.D. student in OPTML Group at Michigan State University, supervised by Prof. Sijia Liu. Before that I spent half a year doing internships at JD AI Research with Dr. Jinfeng Yi. I received my bachelor's degree from Huazhong University of Science and Technology, Wuhan, China. My research interests include Deep Learning and Computer Vision. Now I mainly work on the optimization theories and the algorithmic foundation of trustworthy machine learning and scalable machine learning.

I am actively looking for research internships in CV/ML/DL for summer 2023!

News

  • Aug. 2022: Grateful to receive the Best Paper Runner-Up Award at UAI’22 in recognition of our work Distributed Adversarial Training to Robustify Deep Neural Networks at Scale.
  • June 2022: Student scholarship received from UAI2022!
  • May 2022: One paper is accepted by UAI 2022! An Oral acceptance!
  • May 2022: One paper is accepted by ICML 2022!
  • Apr. 2022: I will serve as the student chair of AdvML Frontiers Workshop at ICML 2022 !
  • Mar. 2022: One paper is accepted by CVPR 2022!
  • Nov. 2021: Our Fast-BAT paper is on the arxiv now.
  • Education
    Ph.D in Computer Science
    East Lansing, MI, USA
    Master of Engineering in Automation
    Aachen, Germany
    Bachalor of Engineering
    Wuhan, China
    Selected Publications
    ( show selected / show all by date / show all by topic )

    Topics: Trustworthy Machine Learning / Scalable Machine Learning / (* indicates equal contribution.)




    More About Me
  • Prior to pursuing a Ph.D., I primarily worked on C++ and wrote a series of Chinese blogs here.
  • I am a huge fan of LEE Chong-Wei, the Malaysian badminton athlete. I participate in physical and badminton training every morning. I am too busy with research after I started my Ph.D. and only play badminton on a weekly basis now.
  • Invited Talk
  • [Feb 2022] "Interpret and advance the algorithmic foundation of adversarial training through bi-level optimization." at UCSB